OpenAI opens ChatGPT as a public research preview
OpenAI makes ChatGPT freely available as a research preview, using a GPT-3.5-series model trained with supervised dialogue data and reinforcement learning from human feedback.
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OpenAI makes ChatGPT freely available as a research preview, using a GPT-3.5-series model trained with supervised dialogue data and reinforcement learning from human feedback.
Stability AI released Stable Diffusion 2.0 with a new text encoder, 512- and 768-pixel generation models, and several image-editing models.
OpenAI makes DALL·E image generation and editing available to all API customers for integration into applications and products.
Google instruction-tuned the T5 family on 1,836 tasks and released five checkpoints ranging from 80 million to 11 billion parameters.
OpenAI removes the DALL·E beta waitlist, allowing users to sign up immediately; more than 1.5M active users were generating over 2M images per day.
OpenAI released and open-sourced Whisper, an automatic speech recognition model for multilingual transcription, language identification, and speech translation into English.
Stability AI publicly releases Stable Diffusion, bringing an open-weight image-generation model to developers and creator communities.
Midjourney opens public testing and provides a low-barrier text-to-image service through Discord.
Zhipu AI releases a 130-billion-parameter dialogue model built for Chinese and English, establishing the first generation of the ChatGLM line.
Google Research announces Imagen, a text-to-image diffusion model focused on photorealism and language understanding; its code and public demo were not released at launch.
Meta releases the 125M-to-175B OPT family; smaller checkpoints and code are available, while OPT-175B is limited to approved noncommercial research access.
DeepMind introduced Flamingo, an 80-billion-parameter visual language model that used a few examples to handle image, video, and text tasks.
EleutherAI scales an open foundation model to the 20-billion-parameter range.
OpenAI introduces DALL·E 2, built around CLIP image embeddings and a diffusion decoder, and initially opens it only to a small group of invited users.
Google presents a 540B-parameter dense language model trained with Pathways; the initial release is a research disclosure, without public weights or a general-purpose API.
Google DeepMind releases a model and scaling-law result arguing that parameter count and training data should grow in proportion.
DeepMind introduced the code-generation system AlphaCode, which performed at about the median level of participants in Codeforces competitions.
OpenAI releases a model trained with reinforcement learning from human feedback to better follow user intent.
The paper documents LaMDA as a dialogue-focused model family with up to 137B parameters and examines response quality, safety and factual grounding.
DeepMind introduced Gopher, a 280-billion-parameter language model, and published research on its capabilities, limitations, and risks without releasing public weights or an API.